Automated Author ProfileUniversity Of Hawaii At Manoa
University Of Hawaii At Manoa
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 96.3 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Abyssal sediments, polymetallic nodules, and water-column samples were collected from the UKSRL1 claim area within the Clarion-Clipperton fracture zone in the Pacific Ocean.
Authors
- University of Hawaii at Manoa
We evaluated the potential for abrupt increases in inorganic N sources to induce cascading effects on DOM and microbial communities in the surface ocean. We collected water from 5 m depth in the central North Pacific and amended duplicate 20 L polycarbonate carboys with nitrate or ammonium, tracking planktonic carbon fixation DOM production DOM composition and microbial community structure responses over 1 week relative to controls
Authors
- University of Hawaii at Manoa
Although a growing body of evidence has indicated that tuna can thermoregulate and have body temperatures that are decoupled from immediate changes in ambient temperature, demonstrating the extend and time-course of body temperature changes in tuna moving through theri natural environments had proved to be elusive. Here we use body temperature data telemetered from free-swimming fish to demonstrate short-latency physiological thermoregulation in bigeye tuna. We used a recently developmed modeling system to determine the magnitude and time-course of the whole-body thermal conductivity changes that would result in body temperature changes observed in fish in the wild. The results indicate rapid, 100 to 1000-fold changes in whole-body thermal conductivity that occur in response to quickly changing ambient temperatures. Coupling this physiological response with behavioral thermoregulation expands the forage space of these animals by permitting acivity in wide ranges of water temperatures and depths.
Authors
- University Of Hawaii At Manoa ;
- Holland, Kim